Electromagnetic measurements of coins can be used to determine whether a coin is a genuine coin and belonging to a certain class or denomination. Typically, an inductance is mounted in proximity to a coin path so that the field generated by applying a drive signal to the inductance is influenced by the coin as it passes.
The coil can be driven using a drive signal that contains a broad spectrum of frequencies, e.g. by applying a square wave drive signal containing multiple harmonics. The influence of the coin on the field can then be sampled at successive time instants relative to the transitions in the drive signal. The samples taken at different times are predominantly influenced by material at different depths within the coin. This time-domain measuring technique can have advantages as compared to frequency-domain measurements using analog filters.
Parameters of the measurement samples can be compared against parameters of the reference measurements in different ways in order to determine whether a coin is a genuine coin and belonging to a certain class or denomination. For example, reference waveforms can be obtained by taking measurements of actual samples of a coin, and can be subsequently stored on the coin tester. These reference waveforms can be compared against the waveforms obtained by the coin tester when a coin under test is brought into proximity with the coin sensor to determine whether a coin falls within a classification of any particular denomination.
Employing such an approach bears several disadvantages. First, such an approach is predicated upon having access to a physical sample of the coin when it is being characterized in the lab. However, having access to a physical sample of the coin during characterization may not be possible if the coin has not yet been fabricated.
Second, even if a physical sample of the coin is available for characterization, such an approach involves an iterative process of trial and error, which is time-consuming and expensive. For example, the results of a fabricated physical coin sample that has been characterized using a particular coil construction may reveal that the underlying design of the coil, coin, or any combination thereof does not provide an acceptable degree of discrimination. Therefore, employing such an approach may result in having to carry out multiple iterations of design, fabrication, and characterization of coils and coins until it is determined that the combination of the coil and the coin provide an acceptable degree of discrimination.
Also, since the reference waveforms captured in the lab can be dependent on the driving signal, such an approach requires that the same driving be used on the coin tester. Such a constraint can be disadvantageous in an application where it is desirable to drive the coin sensor using a random signal. This approach can also be disadvantageous in instances where the coin tester is simply not capable of replicating the precise waveform that was used to stimulate the coin sensor in the lab, or to the extent that the replication accuracy drifts over time.
In cases where the conductor radius is infinite with respect to the coil radius, it is possible to use a TREE algorithm to derive an analytical solution to the impedance change of a coil that is driven by a random input. However, the TREE algorithm proposed by Theodoulidis et al., is predicated on an assumption that the size of the conductor is infinitely large relative to the size of the sensor, such that edge effects of the conductor material can be neglected. In other words, the approach proposed by Theodoulidis et al., requires the size of the sensor to be sufficiently small with respect to the size of the conductor, and is unsuitable for applications in which the edge-effects of the conductor are more significant. See, for example, T. P. Theodoulidis, J. R. Bowler The Truncated Region Eigenfunction Expansion method for the solution of boundary value problems in eddy current nondestructive evaluation. Review of Quantitative Nondestructive Evaluation Vo. 24, 2005; T. P. Theodoulidis.
Therefore, there exists a need for more efficient, high performance, cheaper, low complexity coin sensor that is capable of classifying multi-layer coins without using priori knowledge of the input signal. There also exists a need for an efficient solution for designing a coin tester in the absence of having a physical sample of the coins to be accepted. Applicant believes that the present disclosure addresses some of the concerns discussed above and/or other concerns.